The Experts below are selected from a list of 276 Experts worldwide ranked by ideXlab platform
Murugesu Sivapalan - One of the best experts on this subject based on the ideXlab platform.
-
A conceptual investigation of process controls upon Flood Frequency: role of thresholds
Hydrology and Earth System Sciences, 2007Co-Authors: I. Struthers, Murugesu SivapalanAbstract:Abstract. Traditional statistical approaches to Flood Frequency inherently assume homogeneity and stationarity in the Flood generation process. This study illustrates the impact of heterogeneity associated with threshold non-linearities in the storage-discharge relationship associated with the rainfall-runoff process upon Flood Frequency behaviour. For a simplified, non-threshold (i.e. homogeneous) scenario, Flood Frequency can be characterised in terms of rainfall Frequency, the characteristic response time of the catchment, and storm intermittency, modified by the relative strength of evaporation. The Flood Frequency curve is then a consistent transformation of the rainfall Frequency curve, and could be readily described by traditional statistical methods. The introduction of storage thresholds, namely a field capacity storage and a catchment storage capacity, however, results in different Flood Frequency "regions" associated with distinctly different rainfall-runoff response behaviour and different process controls. The return period associated with the transition between these regions is directly related to the Frequency of threshold exceedence. Where threshold exceedence is relatively rare, statistical extrapolation of Flood Frequency on the basis of short historical Flood records risks ignoring this heterogeneity, and therefore significantly underestimating the magnitude of extreme Flood peaks.
-
Linking Flood Frequency to long‐term water balance: Incorporating effects of seasonality
Water Resources Research, 2005Co-Authors: Murugesu Sivapalan, Ralf Merz, Günter Blöschl, Dieter GutknechtAbstract:Derived Flood Frequency models can be used to study climate and land use change effects on the Flood Frequency curve. Intra-annual (i.e., within year) climate variability strongly impacts upon the Flood Frequency characteristics in two ways: in a direct way through the seasonal variability of storm characteristics and indirectly through the seasonality of rainfall and evapotranspiration which then affect the antecedent catchment conditions for individual storm events. In this paper we propose a quasi-analytical derived Flood Frequency model that is able to account for both types of seasonalities. The model treats individual events separately. It consists of a rainfall model with seasonally varying parameters. Increased Flood peaks, as compared to block rainfall, due to random within-storm rainfall time patterns are represented by a factor that is a function of the ratio of storm duration and catchment response time. Event runoff coefficients are allowed to vary seasonally and include a random component. Their statistical characteristics are derived from long-term water balance simulations. The components of the derived Flood Frequency model are integrated in probability space to derive monthly Flood Frequency curves. These are then combined into annual Flood Frequency curves. Comparisons with Monte Carlo simulations using parameters that are typical of Austrian catchments indicate that the approximations used here are appropriate. We perform sensitivity analyses to explore the effects of the interaction of rainfall and antecedent soil moisture seasonalities on the Flood Frequency curve. When the two seasonalities are in phase, there is resonance, which increases the Flood Frequency curve dramatically. We are also able to isolate the contributions of individual months to the annual Flood Frequency curve. Monthly Flood Frequency curves cross over for the parameters chosen here, as extreme Floods tend to mainly occur in summer while less extreme Floods may occur throughout the year.
-
linking Flood Frequency to long term water balance incorporating effects of seasonality
EGS General Assembly Conference Abstracts, 2002Co-Authors: Ralf Merz, Murugesu Sivapalan, Günter Blöschl, Dieter GutknechtAbstract:Derived Flood Frequency models can be used to study climate and land use change effects on the Flood Frequency curve. Intra-annual (i.e., within year) climate variability strongly impacts upon the Flood Frequency characteristics in two ways: in a direct way through the seasonal variability of storm characteristics and indirectly through the seasonality of rainfall and evapotranspiration which then affect the antecedent catchment conditions for individual storm events. In this paper we propose a quasi-analytical derived Flood Frequency model that is able to account for both types of seasonalities. The model treats individual events separately. It consists of a rainfall model with seasonally varying parameters. Increased Flood peaks, as compared to block rainfall, due to random within-storm rainfall time patterns are represented by a factor that is a function of the ratio of storm duration and catchment response time. Event runoff coefficients are allowed to vary seasonally and include a random component. Their statistical characteristics are derived from long-term water balance simulations. The components of the derived Flood Frequency model are integrated in probability space to derive monthly Flood Frequency curves. These are then combined into annual Flood Frequency curves. Comparisons with Monte Carlo simulations using parameters that are typical of Austrian catchments indicate that the approximations used here are appropriate. We perform sensitivity analyses to explore the effects of the interaction of rainfall and antecedent soil moisture seasonalities on the Flood Frequency curve. When the two seasonalities are in phase, there is resonance, which increases the Flood Frequency curve dramatically. We are also able to isolate the contributions of individual months to the annual Flood Frequency curve. Monthly Flood Frequency curves cross over for the parameters chosen here, as extreme Floods tend to mainly occur in summer while less extreme Floods may occur throughout the year.
Dieter Gutknecht - One of the best experts on this subject based on the ideXlab platform.
-
Linking Flood Frequency to long‐term water balance: Incorporating effects of seasonality
Water Resources Research, 2005Co-Authors: Murugesu Sivapalan, Ralf Merz, Günter Blöschl, Dieter GutknechtAbstract:Derived Flood Frequency models can be used to study climate and land use change effects on the Flood Frequency curve. Intra-annual (i.e., within year) climate variability strongly impacts upon the Flood Frequency characteristics in two ways: in a direct way through the seasonal variability of storm characteristics and indirectly through the seasonality of rainfall and evapotranspiration which then affect the antecedent catchment conditions for individual storm events. In this paper we propose a quasi-analytical derived Flood Frequency model that is able to account for both types of seasonalities. The model treats individual events separately. It consists of a rainfall model with seasonally varying parameters. Increased Flood peaks, as compared to block rainfall, due to random within-storm rainfall time patterns are represented by a factor that is a function of the ratio of storm duration and catchment response time. Event runoff coefficients are allowed to vary seasonally and include a random component. Their statistical characteristics are derived from long-term water balance simulations. The components of the derived Flood Frequency model are integrated in probability space to derive monthly Flood Frequency curves. These are then combined into annual Flood Frequency curves. Comparisons with Monte Carlo simulations using parameters that are typical of Austrian catchments indicate that the approximations used here are appropriate. We perform sensitivity analyses to explore the effects of the interaction of rainfall and antecedent soil moisture seasonalities on the Flood Frequency curve. When the two seasonalities are in phase, there is resonance, which increases the Flood Frequency curve dramatically. We are also able to isolate the contributions of individual months to the annual Flood Frequency curve. Monthly Flood Frequency curves cross over for the parameters chosen here, as extreme Floods tend to mainly occur in summer while less extreme Floods may occur throughout the year.
-
linking Flood Frequency to long term water balance incorporating effects of seasonality
EGS General Assembly Conference Abstracts, 2002Co-Authors: Ralf Merz, Murugesu Sivapalan, Günter Blöschl, Dieter GutknechtAbstract:Derived Flood Frequency models can be used to study climate and land use change effects on the Flood Frequency curve. Intra-annual (i.e., within year) climate variability strongly impacts upon the Flood Frequency characteristics in two ways: in a direct way through the seasonal variability of storm characteristics and indirectly through the seasonality of rainfall and evapotranspiration which then affect the antecedent catchment conditions for individual storm events. In this paper we propose a quasi-analytical derived Flood Frequency model that is able to account for both types of seasonalities. The model treats individual events separately. It consists of a rainfall model with seasonally varying parameters. Increased Flood peaks, as compared to block rainfall, due to random within-storm rainfall time patterns are represented by a factor that is a function of the ratio of storm duration and catchment response time. Event runoff coefficients are allowed to vary seasonally and include a random component. Their statistical characteristics are derived from long-term water balance simulations. The components of the derived Flood Frequency model are integrated in probability space to derive monthly Flood Frequency curves. These are then combined into annual Flood Frequency curves. Comparisons with Monte Carlo simulations using parameters that are typical of Austrian catchments indicate that the approximations used here are appropriate. We perform sensitivity analyses to explore the effects of the interaction of rainfall and antecedent soil moisture seasonalities on the Flood Frequency curve. When the two seasonalities are in phase, there is resonance, which increases the Flood Frequency curve dramatically. We are also able to isolate the contributions of individual months to the annual Flood Frequency curve. Monthly Flood Frequency curves cross over for the parameters chosen here, as extreme Floods tend to mainly occur in summer while less extreme Floods may occur throughout the year.
N. K. Goel - One of the best experts on this subject based on the ideXlab platform.
-
Regional Flood Frequency Analysis using Soft Computing Techniques
Water Resources Management, 2015Co-Authors: Rakesh Kumar, N. K. Goel, Chandranath Chatterjee, P. C. NayakAbstract:For design of various types of hydraulic structures as well as for taking different Flood management measures Flood Frequency estimates are required. Regional Flood Frequency analysis is carried out employing L-moments and soft computing techniques viz. artificial neural network (ANN) and fuzzy inference system (FIS) for the lower Godavari subzone 3(f) of India. The study area covers an areal extent of 174,201 km2 and annual maximum peak Flood data of 17 catchments ranging in size from 35 to 824 km2 are used. The data screening is carried out employing L-moments based Discordancy measure (Di) and regional homogeneity is examined based on the heterogeneity measure (H). On the basis of the L-moment ratio diagram and Zidist –statistic criteria, Pearson Type III (PE3) distribution is chosen as the suitable Frequency distribution for the region. For the region under study, a relationship is developed between mean annual maximum peak Flood and area of the catchment using the Levenberg-Marquardt (LM) iteration and the same is coupled with the PE3 based regional Flood Frequency relationship developed for estimation of Floods of various frequencies for the ungauged catchments of the region. The regional Flood Frequency relationships developed based on L-moments and soft computing techniques are compared.
-
Flood Frequency analysis for the Red River at Winnipeg
Canadian Journal of Civil Engineering, 2001Co-Authors: Donald H. Burn, N. K. GoelAbstract:This paper reviews the Flood Frequency characteristics of the Red River at Winnipeg. The impacts of persistence in the Flood series on estimates of Flood quantiles and their associated confidence intervals are examined. This is done by generating a large number of data sequences using a mixed noise model that preserves the short-term and long-term correlation structures of the observed Flood series. The results reveal that persistence in the data series can lead to a slight increase in the expected Flood magnitude for a given return period. More importantly, persistence is shown to dramatically increase the uncertainty associated with estimated Flood quantiles. The 117-year Flood series for the Red River at Winnipeg is demonstrated to be equivalent to roughly 45 years of independent data.Key words: Flood Frequency, extreme events, simulation, historical data.
-
Derivation of a curve number and kinematic-wave based Flood Frequency distribution
Hydrological Sciences Journal, 2001Co-Authors: R. S. Kurothe, N. K. Goel, B. S. MathurAbstract:The physically-based Flood Frequency models use readily available rainfall data and catchment characteristics to derive the Flood Frequency distribution. In the present study, a new physically-based Flood Frequency distribution has been developed. This model uses bivariate exponential distribution for rainfall intensity and duration, and the Soil Conservation Service-Curve Number (SCS-CN) method for deriving the probability density function (pdf) of effective rainfall. The effective rainfall-runoff model is based on kinematic-wave theory. The results of application of this derived model to three Indian basins indicate that the model is a useful alternative for estimating Flood flow quantiles at ungauged sites.
-
Derived Flood Frequency distribution for negatively correlated rainfall intensity and duration
Water Resources Research, 1997Co-Authors: R. S. Kurothe, N. K. Goel, B. S. MathurAbstract:Derived Flood Frequency distributions (DFFD) are relatively new in the field of hydrology. These models use rainfall and catchment characteristics for deriving the Flood Frequency distribution. The DFFD models developed so far use joint probability density function of exponentially distributed rainfall intensity and duration and consider these variables as independent of each other. In reality this may not be true and these variables may be correlated as well. In the present paper a physically based Flood Frequency model has been developed for negatively correlated rainfall intensity and duration. In the model, infiltration losses are represented by the Φ index. The geomorphoclimatic instantaneous unit hydrograph (GcIUH) is used as the effective rainfall-runoff model.
B. S. Mathur - One of the best experts on this subject based on the ideXlab platform.
-
Derivation of a curve number and kinematic-wave based Flood Frequency distribution
Hydrological Sciences Journal, 2001Co-Authors: R. S. Kurothe, N. K. Goel, B. S. MathurAbstract:The physically-based Flood Frequency models use readily available rainfall data and catchment characteristics to derive the Flood Frequency distribution. In the present study, a new physically-based Flood Frequency distribution has been developed. This model uses bivariate exponential distribution for rainfall intensity and duration, and the Soil Conservation Service-Curve Number (SCS-CN) method for deriving the probability density function (pdf) of effective rainfall. The effective rainfall-runoff model is based on kinematic-wave theory. The results of application of this derived model to three Indian basins indicate that the model is a useful alternative for estimating Flood flow quantiles at ungauged sites.
-
Derived Flood Frequency distribution for negatively correlated rainfall intensity and duration
Water Resources Research, 1997Co-Authors: R. S. Kurothe, N. K. Goel, B. S. MathurAbstract:Derived Flood Frequency distributions (DFFD) are relatively new in the field of hydrology. These models use rainfall and catchment characteristics for deriving the Flood Frequency distribution. The DFFD models developed so far use joint probability density function of exponentially distributed rainfall intensity and duration and consider these variables as independent of each other. In reality this may not be true and these variables may be correlated as well. In the present paper a physically based Flood Frequency model has been developed for negatively correlated rainfall intensity and duration. In the model, infiltration losses are represented by the Φ index. The geomorphoclimatic instantaneous unit hydrograph (GcIUH) is used as the effective rainfall-runoff model.
Bernard Bobee - One of the best experts on this subject based on the ideXlab platform.
-
regional Flood Frequency estimation with canonical correlation analysis
Journal of Hydrology, 2001Co-Authors: Taha B M J Ouarda, Claude Girard, George Cavadias, Bernard BobeeAbstract:Despite its potential advantages, canonical correlation analysis (CCA) has been little used in the fields of hydrology and water resources. In a regional Flood Frequency analysis, canonical correlations can be used to investigate the correlation structure between the two sets of variables represented by watershed characteristics and Flood peaks. This paper presents a clear theoretical framework for the use of canonical correlations in regional Flood Frequency analysis. Some additional results are also presented for the case of gauged target-basins. The approach described in this paper allows one to carry out the determination of homogeneous hydrologic neighborhoods and identifies the variables to use during the step of regional estimation. A data set of 106 stations from the province of Ontario (Canada) is used to demonstrate the advantages of this method and investigate various aspects in relation with its robustness. Results indicate that the method is robust to such factors as the number of stations and the type of parametric distribution being used. Step-by-step algorithms for the delineation of hydrologic neighborhoods in the cases of gauged and ungauged basins are also presented.
-
Recent advances in Flood Frequency analysis
Reviews of Geophysics, 1995Co-Authors: Bernard Bobee, Peter F. RasmussenAbstract:Research on Flood Frequency analysis has taken place with varying intensity over the last couple of decades. The eighties proved to be important years with many significant contributions, reviewed for instance by Greis [1983], Potter [1987], Kirby and Moss [1987], Cunnane [1987], NRC [1988], WMO [1989], and Bobee and Ashkar [1991]. Due to its large economical and environmental impact, Flood Frequency analysis remains a subject of great importance and interest, and the research on improved methods for obtaining reliable Flood estimates has continued into the nineties, although with different emphasis. In the seventies and eighties much effort was spent on developing efficient at-site Flood Frequency procedures. New distributions and estimation methods were introduced in the hydrologic journals, some of them developed specifically for Flood Frequency analysis. It seems that this tendency has decelerated somewhat in the beginning of the nineties. Researchers are increasingly realizing that the lack of sufficiently long data series imposes an upper limit on the degree of sophistication that can reasonably be justified in at-site Flood Frequency analysis. It has been emphasized by many that instead of developing new methodologies for Flood Frequency analysis, effort should be spent on comparing existing ones and on looking for other sources of information [Potter, 1987; Bobee et al, 1993a]. Regionalization is probably the most viable avenue for improving Flood estimates, and fortunately this seems to be the direction that the research in Flood Frequency analysis has taken in the nineties.